On Improving the Training of Models for the Semantic Segmentation of Benthic Communities from Orthographic Imagery

On Improving the Training of Models for the Semantic Segmentation of Benthic Communities from Orthographic Imagery

The semantic segmentation of underwater imagery is an important step in the ecological analysis of coral habitats. To date, scientists produce fine-scale area annotations <i>manually</i>, an exceptionally time-consuming task that could be efficiently automatized by modern CNNs. This pape...

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Bibliographic Details
Main Authors: Gaia Pavoni, Massimiliano Corsini, Marco Callieri, Giuseppe Fiameni, Clinton Edwards, Paolo Cignoni
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Remote Sensing
Subjects:
coral reef monitoring
orthomosaics
orthoprojections
semantic segmentation
deep learning
Online Access:https://www.mdpi.com/2072-4292/12/18/3106

Internet

https://www.mdpi.com/2072-4292/12/18/3106

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